Pandas Profiling Report

Dataset statistics

Number of variables	20
Number of observations	5630
Missing cells	1856
Missing cells (%)	1.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	879.8 KiB
Average record size in memory	160.0 B

Variable types

Numeric	11
Categorical	9

Warnings

`Tenure` has 264 (4.7%) missing values	Missing
`WarehouseToHome` has 251 (4.5%) missing values	Missing
`HourSpendOnApp` has 255 (4.5%) missing values	Missing
`OrderAmountHikeFromlastYear` has 265 (4.7%) missing values	Missing
`CouponUsed` has 256 (4.5%) missing values	Missing
`OrderCount` has 258 (4.6%) missing values	Missing
`DaySinceLastOrder` has 307 (5.5%) missing values	Missing
`CustomerID` is uniformly distributed	Uniform
`CustomerID` has unique values	Unique
`Tenure` has 508 (9.0%) zeros	Zeros
`CouponUsed` has 1030 (18.3%) zeros	Zeros
`DaySinceLastOrder` has 496 (8.8%) zeros	Zeros

Reproduction

Analysis started	2021-02-22 03:44:25.615083
Analysis finished	2021-02-22 03:44:49.826625
Duration	24.21 seconds
Software version	pandas-profiling v2.10.1
Download configuration	config.yaml

CustomerID
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	5630
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	52815.5
Minimum	50001
Maximum	55630
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	50001
5-th percentile	50282.45
Q1	51408.25
median	52815.5
Q3	54222.75
95-th percentile	55348.55
Maximum	55630
Range	5629
Interquartile range (IQR)	2814.5

Descriptive statistics

Standard deviation	1625.385339
Coefficient of variation (CV)	0.03077477897
Kurtosis	-1.2
Mean	52815.5
Median Absolute Deviation (MAD)	1407.5
Skewness	0
Sum	297351265
Variance	2641877.5
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
51199	1	< 0.1%
54027	1	< 0.1%
54011	1	< 0.1%
51964	1	< 0.1%
54015	1	< 0.1%
51968	1	< 0.1%
54019	1	< 0.1%
51972	1	< 0.1%
54023	1	< 0.1%
51976	1	< 0.1%
Other values (5620)	5620	99.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
50001	1	< 0.1%
50002	1	< 0.1%
50003	1	< 0.1%
50004	1	< 0.1%
50005	1	< 0.1%

Value	Count	Frequency (%)
55630	1	< 0.1%
55629	1	< 0.1%
55628	1	< 0.1%
55627	1	< 0.1%
55626	1	< 0.1%

Churn
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

0	4682
1	948

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	5630
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	1

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Most occurring characters

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5630	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	5630	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5630	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	4682	83.2%
1	948	16.8%

Tenure
Real number (ℝ_≥0)

MISSING
ZEROS

Distinct	36
Distinct (%)	0.7%
Missing	264
Missing (%)	4.7%
Infinite	0
Infinite (%)	0.0%

Mean	10.18989937
Minimum	0
Maximum	61
Zeros	508
Zeros (%)	9.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	2
median	9
Q3	16
95-th percentile	27
Maximum	61
Range	61
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	8.557240984
Coefficient of variation (CV)	0.8397767904
Kurtosis	-0.007369469517
Mean	10.18989937
Median Absolute Deviation (MAD)	7
Skewness	0.7365133839
Sum	54679
Variance	73.22637326
Monotocity	Not monotonic

Histogram with fixed size bins (bins=36)

Value	Count	Frequency (%)
1	690	12.3%
0	508	9.0%
8	263	4.7%
9	247	4.4%
7	221	3.9%
10	213	3.8%
5	204	3.6%
4	203	3.6%
3	195	3.5%
11	194	3.4%
Other values (26)	2428	43.1%
(Missing)	264	4.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	508	9.0%
1	690	12.3%
2	167	3.0%
3	195	3.5%
4	203	3.6%

Value	Count	Frequency (%)
61	1	< 0.1%
60	1	< 0.1%
51	1	< 0.1%
50	1	< 0.1%
31	49	0.9%

PreferredLoginDevice
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

Mobile Phone	2765
Computer	1634
Phone	1231

Length

Max length	12
Median length	8
Mean length	9.308525755
Min length	5

Characters and Unicode

Total characters	52407
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mobile Phone
2nd row	Phone
3rd row	Phone
4th row	Phone
5th row	Phone

Value	Count	Frequency (%)
Mobile Phone	2765	49.1%
Computer	1634	29.0%
Phone	1231	21.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
phone	3996	47.6%
mobile	2765	32.9%
computer	1634	19.5%

Most occurring characters

Value	Count	Frequency (%)
o	8395	16.0%
e	8395	16.0%
P	3996	7.6%
h	3996	7.6%
n	3996	7.6%
M	2765	5.3%
b	2765	5.3%
i	2765	5.3%
l	2765	5.3%
	2765	5.3%
Other values (6)	9804	18.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	41247	78.7%
Uppercase Letter	8395	16.0%
Space Separator	2765	5.3%

Most frequent character per category

Value	Count	Frequency (%)
o	8395	20.4%
e	8395	20.4%
h	3996	9.7%
n	3996	9.7%
b	2765	6.7%
i	2765	6.7%
l	2765	6.7%
m	1634	4.0%
p	1634	4.0%
u	1634	4.0%
Other values (2)	3268	7.9%

Value	Count	Frequency (%)
P	3996	47.6%
M	2765	32.9%
C	1634	19.5%

Value	Count	Frequency (%)
	2765	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	49642	94.7%
Common	2765	5.3%

Most frequent character per script

Value	Count	Frequency (%)
o	8395	16.9%
e	8395	16.9%
P	3996	8.0%
h	3996	8.0%
n	3996	8.0%
M	2765	5.6%
b	2765	5.6%
i	2765	5.6%
l	2765	5.6%
C	1634	3.3%
Other values (5)	8170	16.5%

Value	Count	Frequency (%)
	2765	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	52407	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	8395	16.0%
e	8395	16.0%
P	3996	7.6%
h	3996	7.6%
n	3996	7.6%
M	2765	5.3%
b	2765	5.3%
i	2765	5.3%
l	2765	5.3%
	2765	5.3%
Other values (6)	9804	18.7%

CityTier
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

1	3666
3	1722
2	242

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	5630
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	1
3rd row	1
4th row	3
5th row	1

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

Most occurring characters

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5630	100.0%

Most frequent character per category

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	5630	100.0%

Most frequent character per script

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5630	100.0%

Most frequent character per block

Value	Count	Frequency (%)
1	3666	65.1%
3	1722	30.6%
2	242	4.3%

WarehouseToHome
Real number (ℝ_≥0)

MISSING

Distinct	34
Distinct (%)	0.6%
Missing	251
Missing (%)	4.5%
Infinite	0
Infinite (%)	0.0%

Mean	15.63989589
Minimum	5
Maximum	127
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	5
5-th percentile	6
Q1	9
median	14
Q3	20
95-th percentile	33
Maximum	127
Range	122
Interquartile range (IQR)	11

Descriptive statistics

Standard deviation	8.531475187
Coefficient of variation (CV)	0.545494372
Kurtosis	9.986930421
Mean	15.63989589
Median Absolute Deviation (MAD)	5
Skewness	1.619153668
Sum	84127
Variance	72.78606886
Monotocity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
9	559	9.9%
8	444	7.9%
7	389	6.9%
16	322	5.7%
14	299	5.3%
6	295	5.2%
15	288	5.1%
10	274	4.9%
13	249	4.4%
11	233	4.1%
Other values (24)	2027	36.0%
(Missing)	251	4.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	8	0.1%
6	295	5.2%
7	389	6.9%
8	444	7.9%
9	559	9.9%

Value	Count	Frequency (%)
127	1	< 0.1%
126	1	< 0.1%
36	51	0.9%
35	93	1.7%
34	63	1.1%

PreferredPaymentMode
Categorical

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

Debit Card	2314
Credit Card	1501
E wallet	614
UPI	414
COD	365
Other values (2)	422

Length

Max length	16
Median length	10
Mean length	8.85079929
Min length	2

Characters and Unicode

Total characters	49830
Distinct characters	23
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Debit Card
2nd row	UPI
3rd row	Debit Card
4th row	Debit Card
5th row	CC

Value	Count	Frequency (%)
Debit Card	2314	41.1%
Credit Card	1501	26.7%
E wallet	614	10.9%
UPI	414	7.4%
COD	365	6.5%
CC	273	4.8%
Cash on Delivery	149	2.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
card	3815	36.8%
debit	2314	22.3%
credit	1501	14.5%
e	614	5.9%
wallet	614	5.9%
upi	414	4.0%
cod	365	3.5%
cc	273	2.6%
cash	149	1.4%
delivery	149	1.4%

Most occurring characters

Value	Count	Frequency (%)
C	6376	12.8%
r	5465	11.0%
d	5316	10.7%
e	4727	9.5%
	4727	9.5%
a	4578	9.2%
t	4429	8.9%
i	3964	8.0%
D	2828	5.7%
b	2314	4.6%
Other values (13)	5106	10.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	33678	67.6%
Uppercase Letter	11425	22.9%
Space Separator	4727	9.5%

Most frequent character per category

Value	Count	Frequency (%)
r	5465	16.2%
d	5316	15.8%
e	4727	14.0%
a	4578	13.6%
t	4429	13.2%
i	3964	11.8%
b	2314	6.9%
l	1377	4.1%
w	614	1.8%
s	149	0.4%
Other values (5)	745	2.2%

Value	Count	Frequency (%)
C	6376	55.8%
D	2828	24.8%
E	614	5.4%
U	414	3.6%
P	414	3.6%
I	414	3.6%
O	365	3.2%

Value	Count	Frequency (%)
	4727	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	45103	90.5%
Common	4727	9.5%

Most frequent character per script

Value	Count	Frequency (%)
C	6376	14.1%
r	5465	12.1%
d	5316	11.8%
e	4727	10.5%
a	4578	10.2%
t	4429	9.8%
i	3964	8.8%
D	2828	6.3%
b	2314	5.1%
l	1377	3.1%
Other values (12)	3729	8.3%

Value	Count	Frequency (%)
	4727	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	49830	100.0%

Most frequent character per block

Value	Count	Frequency (%)
C	6376	12.8%
r	5465	11.0%
d	5316	10.7%
e	4727	9.5%
	4727	9.5%
a	4578	9.2%
t	4429	8.9%
i	3964	8.0%
D	2828	5.7%
b	2314	4.6%
Other values (13)	5106	10.2%

Gender
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

Male	3384
Female	2246

Length

Max length	6
Median length	4
Mean length	4.797868561
Min length	4

Characters and Unicode

Total characters	27012
Distinct characters	6
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Male
3rd row	Male
4th row	Male
5th row	Male

Value	Count	Frequency (%)
Male	3384	60.1%
Female	2246	39.9%

Histogram of lengths of the category

Value	Count	Frequency (%)
male	3384	60.1%
female	2246	39.9%

Most occurring characters

Value	Count	Frequency (%)
e	7876	29.2%
a	5630	20.8%
l	5630	20.8%
M	3384	12.5%
F	2246	8.3%
m	2246	8.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	21382	79.2%
Uppercase Letter	5630	20.8%

Most frequent character per category

Value	Count	Frequency (%)
e	7876	36.8%
a	5630	26.3%
l	5630	26.3%
m	2246	10.5%

Value	Count	Frequency (%)
M	3384	60.1%
F	2246	39.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	27012	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	7876	29.2%
a	5630	20.8%
l	5630	20.8%
M	3384	12.5%
F	2246	8.3%
m	2246	8.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	27012	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	7876	29.2%
a	5630	20.8%
l	5630	20.8%
M	3384	12.5%
F	2246	8.3%
m	2246	8.3%

HourSpendOnApp
Real number (ℝ_≥0)

MISSING

Distinct	6
Distinct (%)	0.1%
Missing	255
Missing (%)	4.5%
Infinite	0
Infinite (%)	0.0%

Mean	2.931534884
Minimum	0
Maximum	5
Zeros	3
Zeros (%)	0.1%
Memory size	44.1 KiB

Quantile statistics

Minimum	0
5-th percentile	2
Q1	2
median	3
Q3	3
95-th percentile	4
Maximum	5
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	0.72192585
Coefficient of variation (CV)	0.2462620704
Kurtosis	-0.667076137
Mean	2.931534884
Median Absolute Deviation (MAD)	1
Skewness	-0.02721262163
Sum	15757
Variance	0.5211769329
Monotocity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
3	2687	47.7%
2	1471	26.1%
4	1176	20.9%
1	35	0.6%
5	3	0.1%
0	3	0.1%
(Missing)	255	4.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	0.1%
1	35	0.6%
2	1471	26.1%
3	2687	47.7%
4	1176	20.9%

Value	Count	Frequency (%)
5	3	0.1%
4	1176	20.9%
3	2687	47.7%
2	1471	26.1%
1	35	0.6%

NumberOfDeviceRegistered
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.688987567
Minimum	1
Maximum	6
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	3
median	4
Q3	4
95-th percentile	5
Maximum	6
Range	5
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.023998519
Coefficient of variation (CV)	0.2775825346
Kurtosis	0.5828487316
Mean	3.688987567
Median Absolute Deviation (MAD)	1
Skewness	-0.3969686435
Sum	20769
Variance	1.048572967
Monotocity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
4	2377	42.2%
3	1699	30.2%
5	881	15.6%
2	276	4.9%
1	235	4.2%
6	162	2.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	235	4.2%
2	276	4.9%
3	1699	30.2%
4	2377	42.2%
5	881	15.6%

Value	Count	Frequency (%)
6	162	2.9%
5	881	15.6%
4	2377	42.2%
3	1699	30.2%
2	276	4.9%

PreferedOrderCat
Categorical

Distinct	6
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

Laptop & Accessory	2050
Mobile Phone	1271
Fashion	826
Mobile	809
Grocery	410

Length

Max length	18
Median length	12
Mean length	11.94351687
Min length	6

Characters and Unicode

Total characters	67242
Distinct characters	23
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Laptop & Accessory
2nd row	Mobile
3rd row	Mobile
4th row	Laptop & Accessory
5th row	Mobile

Value	Count	Frequency (%)
Laptop & Accessory	2050	36.4%
Mobile Phone	1271	22.6%
Fashion	826	14.7%
Mobile	809	14.4%
Grocery	410	7.3%
Others	264	4.7%

Histogram of lengths of the category

Value	Count	Frequency (%)
mobile	2080	18.9%
accessory	2050	18.6%
laptop	2050	18.6%
	2050	18.6%
phone	1271	11.6%
fashion	826	7.5%
grocery	410	3.7%
others	264	2.4%

Most occurring characters

Value	Count	Frequency (%)
o	8687	12.9%
e	6075	9.0%
	5371	8.0%
s	5190	7.7%
c	4510	6.7%
p	4100	6.1%
r	3134	4.7%
i	2906	4.3%
a	2876	4.3%
y	2460	3.7%
Other values (13)	21933	32.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	50870	75.7%
Uppercase Letter	8951	13.3%
Space Separator	5371	8.0%
Other Punctuation	2050	3.0%

Most frequent character per category

Value	Count	Frequency (%)
o	8687	17.1%
e	6075	11.9%
s	5190	10.2%
c	4510	8.9%
p	4100	8.1%
r	3134	6.2%
i	2906	5.7%
a	2876	5.7%
y	2460	4.8%
h	2361	4.6%
Other values (4)	8571	16.8%

Value	Count	Frequency (%)
M	2080	23.2%
L	2050	22.9%
A	2050	22.9%
P	1271	14.2%
F	826	9.2%
G	410	4.6%
O	264	2.9%

Value	Count	Frequency (%)
	5371	100.0%

Value	Count	Frequency (%)
&	2050	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	59821	89.0%
Common	7421	11.0%

Most frequent character per script

Value	Count	Frequency (%)
o	8687	14.5%
e	6075	10.2%
s	5190	8.7%
c	4510	7.5%
p	4100	6.9%
r	3134	5.2%
i	2906	4.9%
a	2876	4.8%
y	2460	4.1%
h	2361	3.9%
Other values (11)	17522	29.3%

Value	Count	Frequency (%)
	5371	72.4%
&	2050	27.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	67242	100.0%

Most frequent character per block

Value	Count	Frequency (%)
o	8687	12.9%
e	6075	9.0%
	5371	8.0%
s	5190	7.7%
c	4510	6.7%
p	4100	6.1%
r	3134	4.7%
i	2906	4.3%
a	2876	4.3%
y	2460	3.7%
Other values (13)	21933	32.6%

SatisfactionScore
Categorical

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

3	1698
1	1164
5	1108
4	1074
2	586

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	5630
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	3
3rd row	3
4th row	5
5th row	5

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

Histogram of lengths of the category

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

Most occurring characters

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5630	100.0%

Most frequent character per category

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	5630	100.0%

Most frequent character per script

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5630	100.0%

Most frequent character per block

Value	Count	Frequency (%)
3	1698	30.2%
1	1164	20.7%
5	1108	19.7%
4	1074	19.1%
2	586	10.4%

MaritalStatus
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

Married	2986
Single	1796
Divorced	848

Length

Max length	8
Median length	7
Mean length	6.831616341
Min length	6

Characters and Unicode

Total characters	38462
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Single
2nd row	Single
3rd row	Single
4th row	Single
5th row	Single

Value	Count	Frequency (%)
Married	2986	53.0%
Single	1796	31.9%
Divorced	848	15.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
married	2986	53.0%
single	1796	31.9%
divorced	848	15.1%

Most occurring characters

Value	Count	Frequency (%)
r	6820	17.7%
i	5630	14.6%
e	5630	14.6%
d	3834	10.0%
M	2986	7.8%
a	2986	7.8%
S	1796	4.7%
n	1796	4.7%
g	1796	4.7%
l	1796	4.7%
Other values (4)	3392	8.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	32832	85.4%
Uppercase Letter	5630	14.6%

Most frequent character per category

Value	Count	Frequency (%)
r	6820	20.8%
i	5630	17.1%
e	5630	17.1%
d	3834	11.7%
a	2986	9.1%
n	1796	5.5%
g	1796	5.5%
l	1796	5.5%
v	848	2.6%
o	848	2.6%

Value	Count	Frequency (%)
M	2986	53.0%
S	1796	31.9%
D	848	15.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	38462	100.0%

Most frequent character per script

Value	Count	Frequency (%)
r	6820	17.7%
i	5630	14.6%
e	5630	14.6%
d	3834	10.0%
M	2986	7.8%
a	2986	7.8%
S	1796	4.7%
n	1796	4.7%
g	1796	4.7%
l	1796	4.7%
Other values (4)	3392	8.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	38462	100.0%

Most frequent character per block

Value	Count	Frequency (%)
r	6820	17.7%
i	5630	14.6%
e	5630	14.6%
d	3834	10.0%
M	2986	7.8%
a	2986	7.8%
S	1796	4.7%
n	1796	4.7%
g	1796	4.7%
l	1796	4.7%
Other values (4)	3392	8.8%

NumberOfAddress
Real number (ℝ_≥0)

Distinct	15
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	4.214031972
Minimum	1
Maximum	22
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	6
95-th percentile	10
Maximum	22
Range	21
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.583585513
Coefficient of variation (CV)	0.6130911037
Kurtosis	0.9592292732
Mean	4.214031972
Median Absolute Deviation (MAD)	1
Skewness	1.088639383
Sum	23725
Variance	6.674914101
Monotocity	Not monotonic

Histogram with fixed size bins (bins=15)

Value	Count	Frequency (%)
2	1369	24.3%
3	1278	22.7%
4	588	10.4%
5	571	10.1%
6	382	6.8%
1	371	6.6%
8	280	5.0%
7	256	4.5%
9	239	4.2%
10	194	3.4%
Other values (5)	102	1.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	371	6.6%
2	1369	24.3%
3	1278	22.7%
4	588	10.4%
5	571	10.1%

Value	Count	Frequency (%)
22	1	< 0.1%
21	1	< 0.1%
20	1	< 0.1%
19	1	< 0.1%
11	98	1.7%

Complain
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	44.1 KiB

0	4026
1	1604

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	5630
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	0
5th row	0

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

Most occurring characters

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5630	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	5630	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5630	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	4026	71.5%
1	1604	28.5%

OrderAmountHikeFromlastYear
Real number (ℝ_≥0)

MISSING

Distinct	16
Distinct (%)	0.3%
Missing	265
Missing (%)	4.7%
Infinite	0
Infinite (%)	0.0%

Mean	15.70792171
Minimum	11
Maximum	26
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	11
5-th percentile	11
Q1	13
median	15
Q3	18
95-th percentile	23
Maximum	26
Range	15
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.675485463
Coefficient of variation (CV)	0.2339892908
Kurtosis	-0.2803811889
Mean	15.70792171
Median Absolute Deviation (MAD)	3
Skewness	0.7907853591
Sum	84273
Variance	13.50919339
Monotocity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
14	750	13.3%
13	741	13.2%
12	728	12.9%
15	542	9.6%
11	391	6.9%
16	333	5.9%
18	321	5.7%
19	311	5.5%
17	297	5.3%
20	243	4.3%
Other values (6)	708	12.6%
(Missing)	265	4.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
11	391	6.9%
12	728	12.9%
13	741	13.2%
14	750	13.3%
15	542	9.6%

Value	Count	Frequency (%)
26	33	0.6%
25	73	1.3%
24	84	1.5%
23	144	2.6%
22	184	3.3%

CouponUsed
Real number (ℝ_≥0)

MISSING
ZEROS

Distinct	17
Distinct (%)	0.3%
Missing	256
Missing (%)	4.5%
Infinite	0
Infinite (%)	0.0%

Mean	1.751023446
Minimum	0
Maximum	16
Zeros	1030
Zeros (%)	18.3%
Memory size	44.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	2
95-th percentile	6
Maximum	16
Range	16
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.894621447
Coefficient of variation (CV)	1.08200804
Kurtosis	9.132281171
Mean	1.751023446
Median Absolute Deviation (MAD)	1
Skewness	2.545652562
Sum	9410
Variance	3.589590428
Monotocity	Not monotonic

Histogram with fixed size bins (bins=17)

Value	Count	Frequency (%)
1	2105	37.4%
2	1283	22.8%
0	1030	18.3%
3	327	5.8%
4	197	3.5%
5	129	2.3%
6	108	1.9%
7	89	1.6%
8	42	0.7%
10	14	0.2%
Other values (7)	50	0.9%
(Missing)	256	4.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1030	18.3%
1	2105	37.4%
2	1283	22.8%
3	327	5.8%
4	197	3.5%

Value	Count	Frequency (%)
16	2	< 0.1%
15	1	< 0.1%
14	5	0.1%
13	8	0.1%
12	9	0.2%

OrderCount
Real number (ℝ_≥0)

MISSING

Distinct	16
Distinct (%)	0.3%
Missing	258
Missing (%)	4.6%
Infinite	0
Infinite (%)	0.0%

Mean	3.008004468
Minimum	1
Maximum	16
Zeros	0
Zeros (%)	0.0%
Memory size	44.1 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	2
Q3	3
95-th percentile	9
Maximum	16
Range	15
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	2.939679548
Coefficient of variation (CV)	0.9772856323
Kurtosis	4.718466052
Mean	3.008004468
Median Absolute Deviation (MAD)	1
Skewness	2.196414108
Sum	16159
Variance	8.641715846
Monotocity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
2	2025	36.0%
1	1751	31.1%
3	371	6.6%
7	206	3.7%
4	204	3.6%
5	181	3.2%
8	172	3.1%
6	137	2.4%
9	62	1.1%
12	54	1.0%
Other values (6)	209	3.7%
(Missing)	258	4.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1751	31.1%
2	2025	36.0%
3	371	6.6%
4	204	3.6%
5	181	3.2%

Value	Count	Frequency (%)
16	23	0.4%
15	33	0.6%
14	36	0.6%
13	30	0.5%
12	54	1.0%

DaySinceLastOrder
Real number (ℝ_≥0)

MISSING
ZEROS

Distinct	22
Distinct (%)	0.4%
Missing	307
Missing (%)	5.5%
Infinite	0
Infinite (%)	0.0%

Mean	4.543490513
Minimum	0
Maximum	46
Zeros	496
Zeros (%)	8.8%
Memory size	44.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	2
median	3
Q3	7
95-th percentile	11
Maximum	46
Range	46
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.654433197
Coefficient of variation (CV)	0.8043228409
Kurtosis	4.023964341
Mean	4.543490513
Median Absolute Deviation (MAD)	2
Skewness	1.190999503
Sum	24185
Variance	13.35488199
Monotocity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
3	900	16.0%
2	792	14.1%
1	614	10.9%
8	538	9.6%
0	496	8.8%
7	447	7.9%
4	431	7.7%
9	299	5.3%
5	228	4.0%
10	157	2.8%
Other values (12)	421	7.5%
(Missing)	307	5.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	496	8.8%
1	614	10.9%
2	792	14.1%
3	900	16.0%
4	431	7.7%

Value	Count	Frequency (%)
46	1	< 0.1%
31	1	< 0.1%
30	1	< 0.1%
18	10	0.2%
17	17	0.3%

CashbackAmount
Real number (ℝ_≥0)

Distinct	220
Distinct (%)	3.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	177.221492
Minimum	0
Maximum	325
Zeros	4
Zeros (%)	0.1%
Memory size	44.1 KiB

Quantile statistics

Minimum	0
5-th percentile	123
Q1	146
median	163
Q3	196
95-th percentile	292
Maximum	325
Range	325
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	49.19386891
Coefficient of variation (CV)	0.2775841031
Kurtosis	0.9735461687
Mean	177.221492
Median Absolute Deviation (MAD)	23
Skewness	1.149594996
Sum	997757
Variance	2420.036738
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
148	134	2.4%
149	120	2.1%
146	118	2.1%
152	116	2.1%
153	108	1.9%
123	97	1.7%
151	95	1.7%
154	89	1.6%
147	87	1.5%
150	84	1.5%
Other values (210)	4582	81.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4	0.1%
12	1	< 0.1%
25	4	0.1%
37	1	< 0.1%
56	1	< 0.1%

Value	Count	Frequency (%)
325	4	0.1%
324	6	0.1%
323	6	0.1%
322	10	0.2%
321	12	0.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	CustomerID	Churn	Tenure	PreferredLoginDevice	CityTier	WarehouseToHome	PreferredPaymentMode	Gender	HourSpendOnApp	NumberOfDeviceRegistered	PreferedOrderCat	SatisfactionScore	MaritalStatus	NumberOfAddress	Complain	OrderAmountHikeFromlastYear	CouponUsed	OrderCount	DaySinceLastOrder	CashbackAmount
0	50001	1	4.0	Mobile Phone	3	6.0	Debit Card	Female	3.0	3	Laptop & Accessory	2	Single	9	1	11.0	1.0	1.0	5.0	160
1	50002	1	NaN	Phone	1	8.0	UPI	Male	3.0	4	Mobile	3	Single	7	1	15.0	0.0	1.0	0.0	121
2	50003	1	NaN	Phone	1	30.0	Debit Card	Male	2.0	4	Mobile	3	Single	6	1	14.0	0.0	1.0	3.0	120
3	50004	1	0.0	Phone	3	15.0	Debit Card	Male	2.0	4	Laptop & Accessory	5	Single	8	0	23.0	0.0	1.0	3.0	134
4	50005	1	0.0	Phone	1	12.0	CC	Male	NaN	3	Mobile	5	Single	3	0	11.0	1.0	1.0	3.0	130
5	50006	1	0.0	Computer	1	22.0	Debit Card	Female	3.0	5	Mobile Phone	5	Single	2	1	22.0	4.0	6.0	7.0	139
6	50007	1	NaN	Phone	3	11.0	Cash on Delivery	Male	2.0	3	Laptop & Accessory	2	Divorced	4	0	14.0	0.0	1.0	0.0	121
7	50008	1	NaN	Phone	1	6.0	CC	Male	3.0	3	Mobile	2	Divorced	3	1	16.0	2.0	2.0	0.0	123
8	50009	1	13.0	Phone	3	9.0	E wallet	Male	NaN	4	Mobile	3	Divorced	2	1	14.0	0.0	1.0	2.0	127
9	50010	1	NaN	Phone	1	31.0	Debit Card	Male	2.0	5	Mobile	3	Single	2	0	12.0	1.0	1.0	1.0	123

Last rows

	CustomerID	Churn	Tenure	PreferredLoginDevice	CityTier	WarehouseToHome	PreferredPaymentMode	Gender	HourSpendOnApp	NumberOfDeviceRegistered	PreferedOrderCat	SatisfactionScore	MaritalStatus	NumberOfAddress	Complain	OrderAmountHikeFromlastYear	CouponUsed	OrderCount	DaySinceLastOrder	CashbackAmount
5620	55621	0	3.0	Mobile Phone	1	35.0	Credit Card	Female	4.0	5	Mobile Phone	5	Single	3	0	15.0	1.0	2.0	5.0	163
5621	55622	1	14.0	Mobile Phone	3	35.0	E wallet	Male	3.0	5	Fashion	5	Married	6	1	14.0	3.0	NaN	1.0	234
5622	55623	0	13.0	Mobile Phone	3	31.0	E wallet	Female	3.0	5	Grocery	1	Married	2	0	12.0	4.0	NaN	7.0	245
5623	55624	0	5.0	Computer	1	12.0	Credit Card	Male	4.0	4	Laptop & Accessory	5	Single	2	0	20.0	2.0	2.0	NaN	224
5624	55625	0	1.0	Mobile Phone	3	12.0	UPI	Female	2.0	5	Mobile Phone	3	Single	2	0	19.0	2.0	2.0	1.0	155
5625	55626	0	10.0	Computer	1	30.0	Credit Card	Male	3.0	2	Laptop & Accessory	1	Married	6	0	18.0	1.0	2.0	4.0	151
5626	55627	0	13.0	Mobile Phone	1	13.0	Credit Card	Male	3.0	5	Fashion	5	Married	6	0	16.0	1.0	2.0	NaN	225
5627	55628	0	1.0	Mobile Phone	1	11.0	Debit Card	Male	3.0	2	Laptop & Accessory	4	Married	3	1	21.0	1.0	2.0	4.0	186
5628	55629	0	23.0	Computer	3	9.0	Credit Card	Male	4.0	5	Laptop & Accessory	4	Married	4	0	15.0	2.0	2.0	9.0	179
5629	55630	0	8.0	Mobile Phone	1	15.0	Credit Card	Male	3.0	2	Laptop & Accessory	3	Married	4	0	13.0	2.0	2.0	3.0	169

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows